Project Management and Documentation

Objective

Learners will learn about and practice managing their projects using file structure and RStudio projects, and about current best practices and style guides for R coding.

Lesson Outline

Introductions
Discuss reproducibility
Give tour of course website & syllabus
- Point out code of conduct
Briefly demo Slack
Screen setup
Don’t save or load .RData!
Discuss general best practices for research compendia (use Carpentry lesson??)
- All files needed for a project in the same folder (ideally)
- Organize data, code, and outputs into different folders at a minimum
- Never edit raw data
- Include documentation on what each file is/does in a README
  - Project summary
  - Project status (in progress, archived, just an idea?)
  - How to give credit
  - Structure of repo (what files do what?)
  - How to reproduce results
  - Example READMEs:
Live Coding: create an R project and add gapminder data to it
- Show file pane & connect to Windows Explorer / Finder
- Show how to make a file read-only
- Demo closing, opening, and switching projects
Homework:
- Apply one or more of the organizing principles of a research compendium to an existing research project.

Installation & materials

Citation

BibTeX citation:

@online{scott2024,
  author = {Scott, Eric and Diaz, Renata and Guo, Jessica and Riemer,
    Kristina},
  title = {Project {Management} and {Documentation}},
  date = {2024},
  url = {https://cct-datascience.github.io/repro-data-sci/lessons/1-project-management/notes.html},
  doi = {10.5281/zenodo.8411612},
  langid = {en}
}

For attribution, please cite this work as:

Scott, Eric, Renata Diaz, Jessica Guo, and Kristina Riemer. 2024. “Project Management and Documentation.” Reproducibility & Data Science in R. 2024. https://doi.org/10.5281/zenodo.8411612.